Metacognitive AI: Framework and the Case for a Neurosymbolic Approach
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929388886425600 |
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| author | Wei, Hua Shakarian, Paulo Lebiere, Christian Draper, Bruce Krishnaswamy, Nikhil Nirenburg, Sergei |
| author_facet | Wei, Hua Shakarian, Paulo Lebiere, Christian Draper, Bruce Krishnaswamy, Nikhil Nirenburg, Sergei |
| contents | Metacognition is the concept of reasoning about an agent's own internal processes and was originally introduced in the field of developmental psychology. In this position paper, we examine the concept of applying metacognition to artificial intelligence. We introduce a framework for understanding metacognitive artificial intelligence (AI) that we call TRAP: transparency, reasoning, adaptation, and perception. We discuss each of these aspects in-turn and explore how neurosymbolic AI (NSAI) can be leveraged to address challenges of metacognition. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_12147 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Metacognitive AI: Framework and the Case for a Neurosymbolic Approach Wei, Hua Shakarian, Paulo Lebiere, Christian Draper, Bruce Krishnaswamy, Nikhil Nirenburg, Sergei Artificial Intelligence Metacognition is the concept of reasoning about an agent's own internal processes and was originally introduced in the field of developmental psychology. In this position paper, we examine the concept of applying metacognition to artificial intelligence. We introduce a framework for understanding metacognitive artificial intelligence (AI) that we call TRAP: transparency, reasoning, adaptation, and perception. We discuss each of these aspects in-turn and explore how neurosymbolic AI (NSAI) can be leveraged to address challenges of metacognition. |
| title | Metacognitive AI: Framework and the Case for a Neurosymbolic Approach |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2406.12147 |